Extracting Value from Electric Grid Information Towards a Resilient Grid Amidst Decarbonization Efforts

Abstract

Today, decarbonization initiatives pose changes to the power grid, involving a shift away from carbon-based sources of energy. From a generation perspective, this means an increase in the prevalence of renewable generation such as wind and solar photovoltaic generation and a gradual retirement of generation associated with high levels of carbon emission, like coal plants. A parallel trend is beginning in the transportation system as various forms of transportation are beginning to electrify and the penetration of electrification within each form is anticipated to increase sharply. In order to approach, study, and prepare for the effect of resource adequacy in a grid with a high penetration of renewable resources in various weather conditions and the impact of substantial transportation electrification of the power system, scenario-based simulations can be leveraged.

This work employs electric grid models and algorithms to develop scenarios to represent conditions anticipated in the future of the electric grid and provide visualization tools for the understanding and communication of the data involved. Frameworks are developed and presented to prepare scenarios reflecting renewable resource droughts and transportation electrification. Leveraging explicit representation of weather in power flow models, a methodology for calculating the weather-informed capacity of renewable generators is presented and validated. Historic weather data is analyzed and periods with low availability of renewable generation resources, or renewable resource droughts, are identified. Combining the weather-informed generation capacity calculations and historic weather data representing renewable resource droughts, scenarios are generated to evaluate power system behavior under resource drought conditions. A case study is used to identify and simulate historic solar and wind resource droughts, illustrating the importance of including weather data explicitly in power flow models and the framework used to create renewable resource drought scenarios.

Transportation electrification scenarios are developed using a developed framework of largescale high-fidelity models of transportation networks and the electric grid. In order to represent the charging load of electric vehicles on the electric grid, a Voronoi Diagram algorithm is used to map the EV chargers to points of connection on the electric grid by geographic and electrical proximity. An extension of this methodology is demonstrated in the calculation of operational emissions from the transportation network and electric grid on a spatiotemporal basis on a case study including transportation electrification in the greater Houston area.

In order to interpret and communicate the data involved in power systems models and analysis, visual displays serve as an invaluable tool. Particularly in an evolving grid, the understanding and communication of grid data are increasingly important so that informed decisions can be made by researchers, engineers, and policymakers. Visualization frameworks are created and enable researchers and engineers to create value-driven visualizations to help with interpreting the large quantities of data generated from power systems studies. The visualization frameworks also have applications in communicating the information from these studies to diverse audiences. Included in this dissertation are strategies for creating easily-interpreted visual representations of flows in power grids, leveraging a Delaunay triangulation algorithm, which can be applied in the representation of real or reactive power flows, GIC flows, or in representing the results of sensitivity analyses. Also included are considerations for contour creation including discussion of interpolation methods and colormap decisions. The representation of geographically-discrete data is presented through the use of GDV layout algorithms and the introduction of summary objects with an emphasis on providing situational awareness for the engineers and researchers performing analyses. Lastly, a storytelling framework is presented which serves as a representation of ecological interface design principals for emphasis on communicating power systems information with diverse audiences.